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14
A Computationally Efficient Feasible Sequential Quadratic Programming Algorithm
 SIAM Journal on Optimization
, 2001
"... . A sequential quadratic programming (SQP) algorithm generating feasible iterates is described and analyzed. What distinguishes this algorithm from previous feasible SQP algorithms proposed by various authors is a reduction in the amount of computation required to generate a new iterate while the pr ..."
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. A sequential quadratic programming (SQP) algorithm generating feasible iterates is described and analyzed. What distinguishes this algorithm from previous feasible SQP algorithms proposed by various authors is a reduction in the amount of computation required to generate a new iterate while the proposed scheme still enjoys the same global and fast local convergence properties. A preliminary implementation has been tested and some promising numerical results are reported. Key words. sequential quadratic programming, SQP, feasible iterates, feasible SQP, FSQP AMS subject classifications. 49M37, 65K05, 65K10, 90C30, 90C53 PII. S1052623498344562 1.
Symmetrizing the KullbackLeibler Distance
 IEEE Transactions on Information Theory
, 2000
"... We define a new distance measure the resistoraverage distance between two probability distributions that is closely related to the KullbackLeibler distance. While the KullbackLeibler distance is asymmetric in the two distributions, the resistoraverage distance is not. It arises from geometric ..."
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We define a new distance measure the resistoraverage distance between two probability distributions that is closely related to the KullbackLeibler distance. While the KullbackLeibler distance is asymmetric in the two distributions, the resistoraverage distance is not. It arises from geometric considerations similar to those used to derive the Chernoff distance. Determining its relation to wellknown distance measures reveals a new way to depict how commonly used distance measures relate to each other. 1 Introduction The KullbackLeibler distance [15, 16] is perhaps the most frequently used informationtheoretic "distance" measure from a viewpoint of theory. If p 0 , p 1 are two probability densities, the KullbackLeibler distance is defined to be D(p 1 #p 0 )= # p 1 (x)log p 1 (x) p 0 (x) dx . (1) In this paper, log() has base two. The KullbackLeibler distance is but one example of the AliSilvey class of informationtheoretic distance measures [1], which are defined to ...
Toward a Theory of Information Processing
 IEEE Trans. Signal Processing
, 2002
"... Information processing theory endeavors to quantify how well signals encode information and how well systems, by acting on signals, process information. We use informationtheoretic distance measures, the KullbackLeibler distance in particular, to quantify how well signals represent information. ..."
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Information processing theory endeavors to quantify how well signals encode information and how well systems, by acting on signals, process information. We use informationtheoretic distance measures, the KullbackLeibler distance in particular, to quantify how well signals represent information. The ratio of distances between a system's output and input quantifies the system's information processing properties.
Useful Facts about the KullbackLeibler Discrimination Distance
, 2004
"... This report contains a list of some of the more prominent properties and theorems concerning the KullbackLeibler (KL) discrimination distance. A brief discussion is also provided indicating the type of problems in which the KL distance has been applied. References are provided for the reader’s conv ..."
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This report contains a list of some of the more prominent properties and theorems concerning the KullbackLeibler (KL) discrimination distance. A brief discussion is also provided indicating the type of problems in which the KL distance has been applied. References are provided for the reader’s convenience. 1
Optimal Target Placement for Neural Communication Prostheses
, 2006
"... Neural prosthetic systems have been designed to estimate continuous reach trajectories as well as discrete reach targets. In the latter case, reach targets are typically decoded from neural activity during an instructed delay period, before the reach begins. We have recently characterized the decod ..."
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Cited by 4 (4 self)
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Neural prosthetic systems have been designed to estimate continuous reach trajectories as well as discrete reach targets. In the latter case, reach targets are typically decoded from neural activity during an instructed delay period, before the reach begins. We have recently characterized the decoding speed and accuracy achievable by such a system. The results were obtained using canonical target layouts, independent of the tuning properties of the neurons available. Here we seek to increase decode accuracy by judiciously selecting the locations of the reach targets based on the characteristics of the neural population at hand. We present an optimal target placement algorithm that approximately maximizes decode accuracy with respect to target locations. Using maximum likelihood decoding, the optimal target placement algorithm yielded up to 11 and 12 % improvement for two and sixteen targets, respectively. For four and eight targets, gains were more modest (5 and 3%, respectively) as the target layouts found by the algorithm closely resembled the canonical layouts. Thus, the algorithm can serve not only to find target layouts that outperform canonical layouts, but it can also confirm or help select among multiple canonical layouts. These results indicate that the optimal target placement algorithm is a valuable tool for designing highperformance prosthetic systems.
Global and Local Optimization Algorithms for Optimal Signal Set Design
 Journal of Research of the National Institute of Standars and Technology
, 2001
"... this paper, we will assume a peak amplitude constraint, i.e.,  s m [t ] C , m =1,...,M , t =1,...,T , (3) where C > 0 is given. Note that we could just as easily have considered an average energy constraint in our formulation. Our design problem is thus reduced to choosing parameters in ..."
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this paper, we will assume a peak amplitude constraint, i.e.,  s m [t ] C , m =1,...,M , t =1,...,T , (3) where C > 0 is given. Note that we could just as easily have considered an average energy constraint in our formulation. Our design problem is thus reduced to choosing parameters in order to maximize Eq. (1), subject to the constraints Eq. (3)
Algorithms for Understanding Motor Cortical Processing and Neural Prosthetic Systems
, 2009
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To cooperate or not to cooperate: Detection strategies in sensor networks
 in: ICASSP ’04
, 2004
"... This paper is an initial investigation into the following question: Can cooperation among sensors in a sensor network improve detection performance in a simple hypothesis test? We analyze a simple cooperative system using the KullbackLeibler (KL) discrimination distance and a quantity known as the ..."
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This paper is an initial investigation into the following question: Can cooperation among sensors in a sensor network improve detection performance in a simple hypothesis test? We analyze a simple cooperative system using the KullbackLeibler (KL) discrimination distance and a quantity known as the information transfer ratio which is a ratio of KL distances. We discover that, asymptotically, gain over a noncooperative system depends on the conditional KL distance. We conclude with an illustrative example which demonstrates that cooperation not only significantly improves performance but can also degrade it. 1.
Signal Design and Detection in Presence of Nonlinear Phase Noise
"... Abstract—In optical fiber transmission systems using inline amplifiers, the interaction of a signal and amplifier noise through the Kerr effect leads to nonlinear phase noise that can impair the detection of phasemodulated signals. We present analytical expressions for the maximumlikelihood (ML) d ..."
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Abstract—In optical fiber transmission systems using inline amplifiers, the interaction of a signal and amplifier noise through the Kerr effect leads to nonlinear phase noise that can impair the detection of phasemodulated signals. We present analytical expressions for the maximumlikelihood (ML) decision boundaries and symbolerror rate (SER) for phaseshift keying and differential phaseshift keying systems with coherent and differentially coherent detection, respectively. The ML decision boundaries are in the form θ(r) = c2r2 + c1r + c0, where θ and r are the phase and the amplitude of the received signal, respectively. Using the expressions for the SER, we show that the impact of phase error from carrier synchronization is small, particularly for transoceanic links. For modulation formats such as 16quadrature amplitude modulation, we propose various transmitter and receiver phase rotation strategies such that the ML detection is well approximated by using straightline decision boundaries. The problem of signal constellation design for optimal SER performance is also studied for a system with four signal points. Index Terms—Maximum likelihood (ML) detection, nonlinear optics, optical fiber communication, optical Kerr effect, phase noise, quadrature amplitude modulation (QAM). I.
AN INFORMATION PROCESSING APPROACH TO DISTRIBUTED DETECTION
"... We apply the recent theory of information processing to a hybrid distributed detection architecture that combines the traditional parallel and tandem architectures. Central to this theory is the KullbackLeibler discrimination distance and a quantity known as the information transfer ratio, defined ..."
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We apply the recent theory of information processing to a hybrid distributed detection architecture that combines the traditional parallel and tandem architectures. Central to this theory is the KullbackLeibler discrimination distance and a quantity known as the information transfer ratio, defined as the ratio of the KL distances between the distributions characterizing the input and output of a system. We characterize the asymptotic performance of a proposed hybrid system and compare it with the performance of the parallel, tandem and centralized architectures. We conclude with an illustrative example. 1.